dc.contributor.author | Keleshibieke, Yesitai | |
dc.date.accessioned | 2019-03-04T08:59:14Z | |
dc.date.available | 2019-03-04T08:59:14Z | |
dc.date.issued | 2019-01 | |
dc.identifier.citation | Keleshibieke, Yesitai (2019) Wind turbine optimization. Nazarbayev University School of Engineering | en_US |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/3760 | |
dc.description.abstract | Facing the current extreme global environmental and energy crisis, wind energy, as a source of renewable energy, is becoming more and more crucial to the future development of human civilization. Wind energy technology is already well developed and widely used around the world. Currently, horizontal axis wind turbines (HAWT) are the most common and efficient type of wind turbines that are widely used in commercial wind farms. And the key to greater power output and high efficiency lies in the design of wind turbine blades. Thus, the design optimization of wind turbine blades plays a significant role in achieving our goal. In this thesis, the current research status, design theory, and methods are reviewed; and blade efficiency, torques and force coefficients of wind turbine blades are analyzed. This study is based on the momentum-blade element theory and CFD method. The NREL Phase VI blade model is built. A truly 3D optimization platform, consisting of Solidworks, Ansys Fluent and Ansys Workbench/Design Xplorer, is used in the optimization process, in which a direct optimization method is adopted for the aerodynamic optimization of the NREL Phase VI turbine blade. The average power output of the turbine is set as a goal of optimization which should be maximized during the optimization process. To achieve that, the positions of the trailing edges on 20 cross sections are set as independent variables which change within a certain range to achieve maximum power output. As a result, the power output increases by over 9 percent and proves the accuracy and feasibility of the optimization methodology. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | wind turbine optimization | en_US |
dc.subject | numerical simulation | en_US |
dc.subject | CFD | en_US |
dc.subject | BEM | en_US |
dc.subject | IBEM | en_US |
dc.subject | genetic algorithm | en_US |
dc.subject | GDO | en_US |
dc.title | Wind turbine optimization | en_US |
dc.type | Master's thesis | en_US |
workflow.import.source | science |
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